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Security and Privacy

A stable, safe, and resilient cyberspace is vital for our economic and societal wellbeing. This concentration helps students learn how to fortify cyber networks, combat threats, and foster “white hat” hacking. Researching systems allows for students to improve real-world systems to make them stronger and securer. This also includes data-driven analysis of privacy and social networks. After graduation, our students often work either in private corporations or in governments.

Sample research projects:

Damon McCoy, one of the department's newest faculty members, researched counterfeit pharmacy affiliate networks. Online sales of counterfeit or unauthorized products drive a robust underground advertising industry that includes email spam, “black hat” search engine optimization, forum abuse and so on. Virtually everyone has encountered enticements to purchase drugs, prescription-free, from an online “Canadian Pharmacy.” However, even though such sites are clearly economically motivated, the shape of the underlying business enterprise is not well understood precisely because it is “underground.”

Working in digital forensics and recovery, Nasir Memon, CSE department professor, with a team of Ph.D. students, founded the Digital Assembly company. This company works in products that recover digital photos that are fragmented or deleted.

Justin Cappos has been developing an open peer-to-peer computing system, Seattle. Nearly 100 students participated in its creation. The purpose of this project is to make cloud computing available to everyone. It's free and provides access to computers worldwide. This project was funded by the National Science Foundation.

People increasingly make important life decisions based on large amounts of data, using online tools. ProfessorOded Nov works with students and collaborators to explore how novel computational tools and user interface design informed by social science can help people make sense and reason better about such data and their personal implications. In a series of studies, Nov and his doctoral student Junius Gunaratne showed how design informed by research in psychology and economics can help consumers make informed decisions and outperform users of traditional financial user interfaces. In another series of studies, Nov and his doctoral student Martina Balestra and their collaborators showed how design interventions affect users' understanding of and level of engagement with their personal genomic data. In another line of research, Nov and Professor Maurizio Porfiri study how design interventions help impact the behavior of contributors to citizen science projects.

Big Data Management, Analysis, and Visualization

The organization and governance of large volumes of data. This concentration allows for retaining data obtained from a large number of sources—from a large city, to individuals, and anywhere in between—and ensures a high level of data quality for analytical purposes. The visualization of such data elegantly brings structure and simplicity to it.

Sample research projects:

Enrico Bertini, in conjunction with Ph.D. students Christian Felix Da Silva and Anshul Pandey, developed RevEx. A collaboration with ProPublica, this tool visualizes Yelp data and has the ability to single out reviews under specific parameters or keywords. The tool can sort through millions of reviews at one time and visualize trends.

Guido Gerig, department chair, focuses on clinical neuroimaging to assist in studying such areas as early childhood brain development, children with autism, and infants at risk of schizophrenia. His methodology includes image processing, registration, atlas building, segmentation, shape analysis, and statistical analysis.

In this related paper, Gerig studies the early developing brain by displaying the longitudinal MRI scans of the same subject's brain at various ages, from two weeks to two years.

Assistant Professor Rumi Chunara works at the intersection of Big Data and Public Health, using information gleaned from social media sites like Facebook and Twitter to predict epidemics, track obesity rates on a local level, and much more.

In Prof. Chunara's research on US obesity rates, for example, Facebook is used to cross-measure user interests and obesity prevalence within certain metroplitan populations. Activity-related interests across the US and sedentary-related interests across NYC were significantly associated with obesity prevalence.

Semiha Ergan, an affiliate professor of the Computer Science and Engineering Department, is responsible for a project that performs data analysis on highly sensed buildings for understanding patterns in building performance. The data deals with HVAC systems and energy use in such buildings to assist in building management strategies.

Game Engineering and Computational Intelligence

For students who are interested in learning game programming and taking part in game development and design. Computer graphics, human-computer interaction, artificial intelligence, and allied computational fields all play a role in this burgeoning industry. Art and engineering intersect to create innovative game environments that captivate players.

Algorithms and Theoretical Computer Science

The theories of computer science are what make computers possible. Algorithms include computational calculation and automated reasoning, while theoretical computer science deals with the mathematical aspects of computing. These theories help engineers build on our current knowledge of computers in order to invent breakthroughs, paving the way to better and newer solutions.

Sample research projects:

John Iaconois the co-author of "Cache-Oblivious Persistence." Partial persistence is a general transformation that takes a data structure and allows queries to be executed on any past state of the structure. The cache-oblivious model is the leading model of a modern multi-level memory hierarchy. This paper presents the first general transformation for making cache-oblivious model data structures partially persistent.

Boris Aronovco-wrote a paper titled "Improved Bounds for the Union of Locally Fat Objects in the Plane." In this paper, they obtain sharper upper bounds on the complexity of the union of n locally γ-fat objects of constant complexity in the plane, and of nγ-fat triangles in the plane.